Tandem Mass Spectrometry Data Analysis Research Articles

The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data.

The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.

Differentiating samples and experimental protocols by direct comparison of tandem mass spectra.

Peptide tandem mass spectra can be analyzed by a number of means. They can be compared against predicted spectra of peptides derived from genome sequences, compared against previously acquired and identified spectra, or - sometimes - sequenced de novo. We recently introduced another method which compares spectra between liquid chromatography/tandem mass spectrometry (LC/MS/MS) datasets to determine the shared spectral content, and demonstrated how this can be applied in a molecular phylogenetic study using sera from human and non-human primates. We will here explore if such a method have other, serendipitous uses. We used the existing compareMS2 algorithm without modification on a diverse set of experiments. First we conducted a small phylogenetic study, using (mammalian) bone samples to study old material, and human pathogens aiming to distinguish clinically important strains. Although not as straightforward as primate sera analysis, the method shows significant promise for all these applications. We also used the algorithm to compare 24 different protocols for extraction of proteins from muscle tissue. The results provided useful information in comparing protocols. Finally, we applied compareMS2 aiming for quality control of two traceable protein reference standards (troponin) used in clinical chemistry assays, by analysing the effect of storage conditions. The results illustrate a broad applicability of the metric based on shared tandem mass spectra between LC/MS/MS datasets for analysing protein digests in different types of experiments. There is no reason to assume that our instance of this method is optimal in any of these situations, as it makes limited or no use of accurate mass and chromatographic retention time. We propose that with further improvement and refinement, this type of analysis can be applied as a simple but informative first step in many pipelines for bottom-up tandem mass spectrometry data analysis in proteomics and other fields, comparing or analysing large numbers of samples or datasets.

Relative mass defect filtering of mass spectra: a path to discovery of plant specialized metabolites.

The rapid identification of novel plant metabolites and assignments of newly discovered substances to natural product classes present the main bottlenecks to defining plant specialized phenotypes. Although mass spectrometry provides powerful support for metabolite discovery by measuring molecular masses, ambiguities in elemental formulas often fail to reveal the biosynthetic origins of specialized metabolites detected using liquid chromatography-mass spectrometry. A promising approach for mining liquid chromatography-mass spectrometry metabolite profiling data for specific metabolite classes is achieved by calculating relative mass defects (RMDs) from molecular and fragment ions. This strategy enabled the rapid recognition of an extensive range of terpenoid metabolites in complex plant tissue extracts and is independent of retention time, abundance, and elemental formula. Using RMD filtering and tandem mass spectrometry data analysis, 24 novel elemental formulas corresponding to glycosylated sesquiterpenoid metabolites were identified in extracts of the wild tomato Solanum habrochaites LA1777 trichomes. Extensive isomerism was revealed by ultra-high-performance liquid chromatography, leading to evidence of more than 200 distinct sesquiterpenoid metabolites. RMD filtering led to the recognition of the presence of glycosides of two unusual sesquiterpenoid cores that bear limited similarity to known sesquiterpenes in the genus Solanum. In addition, RMD filtering is readily applied to existing metabolomics databases and correctly classified the annotated terpenoid metabolites in the public metabolome database for Catharanthus roseus.